SA-selection-based Genetic Algorithm for the Design of Fuzzy Controller
SA-selection-based Genetic Algorithm for the Design of Fuzzy Controller
复制标题
基于SA选择的遗传算法模糊控制器设计
DOI：
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发表时间：
2005
影响因子：
3.2
通讯作者：
Jung
中科院分区：
文献类型：
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作者：
Chang;Jung
本文提出了一种新的随机方法来解决组合优化问题，即在遗传算法（GA）中使用一种新的选择方法，即SA-选择。该方法将遗传算法与模拟退火算法相结合，提高了遗传算法的性能。GA和SA具有互补的优势和劣势。虽然遗传算法通过搜索点的种群来探索搜索空间，但它的收敛性能很差。相比之下，SA具有良好的收敛特性，但它不能通过人口来探索搜索空间。然而，SA采用了一个完全本地的选择策略，其中当前的候选和新的修改进行评估和比较。为了验证所提出的方法的有效性，被认为是一个模糊控制器的平衡车上的倒立摆的优化。
This paper presents a new stochastic approach for solving combinatorial optimization problems by using a new selection method, i.e. SA-selection, in genetic algorithm (GA). This approach combines GA with simulated annealing (SA) to improve the performance of GA. GA and SA have complementary strengths and weaknesses. While GA explores the search space by means of population of search points, it suffers from poor convergence properties. SA, by contrast, has good convergence properties, but it cannot explore the search space by means of population. However, SA does employ a completely local selection strategy where the current candidate and the new modification are evaluated and compared. To verify the effectiveness of the proposed method, the optimization of a fuzzy controller for balancing an inverted pendulum on a cart is considered.